Criteria for considering studies for this review
Types of studies
We will include randomized controlled clinical trials (RCTc).
Types of participants
We will include studies evaluating adults (older than18 years) with diabetes affected by MCD requiring PCI or CABG.
DM: to be consistent with changes in classification and diagnostic criteria of DM over the years, the diagnosis should be established using the standard criteria valid at the time of the trial commencing (e.g. American Diabetes Association (ADA 1999; ADA 2008); World Health Organization (WHO 1998)). Ideally, diagnostic criteria should have been described. If necessary, we will use the study authors' definition of DM. We plan to subject diagnostic criteria to a sensitivity analysis.
MCD will be defined as the identification of two or more main epicardial vessels (left anterior descending, left circumflex, or right coronary artery) (Kirschbaum 2010).
Types of interventions
PCI (with or without stent).
CABG (any variant of the technique).
We will not include studies comparing PCI or CABG versus medical treatment, no treatment, or other treatments. Concomitant interventions will have to be similar in the intervention and comparator groups to establish fair comparisons.
Types of outcome measures
Nonfatal myocardial infarction.
Health-related quality of life.
Method and timing of outcome measurement
All-cause mortality: defined as death from any cause and measured at 30 days, and one, two, three, four, and five years after the intervention.
Adverse events: apart from hypoglycemic episodes, defined as acute renal failure, perioperative bleeding and infections, stent restenosis, and thrombosis. Measured within the first 30 days and at one year after the intervention.
Stroke: as defined by the study author and measured within the first 30 days after the procedure, at intermedium follow-up (one to three years), and at late follow-up (four to five years).
Nonfatal myocardial infarction: as defined by the study author and measured within the first 30 days after the procedure, at intermedium follow-up (one to three years, and at late follow-up (four to five years).
Symptomatic angina: measured using the Seattle Angina Questionnaire (SAQ) at one month, six months, and one year.
Repeated revascularization: defined as need of revascularization and measured within five years after the initial procedure.
Health-related quality of life: measured with the SAQ or 36-item Short Form (SF-36) at one month, six months, and one year.
Metabolic control: defined as analysis of glycosylated hemoglobin A1c (HbA1c) measured at one year after the procedure.
Socioeconomic effects: defined as cumulative five-year costs, life-years, quality-adjusted life-year (QALY), hospitalization length, and time out of work. Measured within five years after the procedure.
'Summary of findings' table
We will present a 'Summary of findings' table reporting the following critical (for decision-making) outcomes.
Nonfatal myocardial infarction.
Health-related quality of life.
Search methods for identification of studies
We will search the following sources from inception to the present.
The Cochrane Library.
We will also search the following trial registers.
For detailed search strategies, see Appendix 1. We will continuously apply PubMed's 'My NCBI' (National Center for Biotechnology Information) email alert service for identification of newly published studies using a basic search strategy (see Appendix 1). Four weeks before we submit the final review draft to the Cochrane Metabolic and Endocrine Disorders Group (CMED) for editorial approval, we will perform a complete update search on all specified databases. Should we detect new studies for inclusion, we will evaluate these and incorporate findings in our review before submission of the final review draft.
If we detect additional relevant key words during any of the electronic or other searches, we will modify the electronic search strategies to incorporate these terms and document the changes. We will place no restrictions on the language of publication when searching the electronic databases or reviewing reference lists in identified studies.
Searching other resources
In order to identify articles potentially missed through the electronic searches, grey literature and unpublished studies, we will:
handsearch reference lists of all included studies and of relevant reviews retrieved by electronic searching to identify other potentially eligible trials or ancillary publications. We will conduct a search for other systematic reviews and health technology assessment reports in the CRD Database (www.crd.york.ac.uk/crdweb) and Epistemonikos (www.epistemonikos.org). The list of reviews and health technology assessment reports screened will be reported as an appendix.
handsearch conference proceedings for the last five years from the following events: World Congress of Cardiology, European Society of Cardiology (ESC) Congress, and American College of Cardiology (ACC) Annual Scientific Sessions.
contact corresponding authors of included studies, local and foreign experts in the field, and pharmaceutical companies representatives that market coronary stents (e.g. Boston Scientific Corporation, Medtronic, Inc., Abbott Laboratories) for any additional published or unpublished data.
run a Scholar Google search for key terms and authors.
Data collection and analysis
Selection of studies
To determine the studies to be assessed further, two review authors (CB, CR) will independently scan the abstract, title, or both sections of every record retrieved by the searches. We will investigate all potentially eligible articles as full text. We will resolve any discrepancies through consensus or recourse to a third review author (GR). We will use the software EROS (www.eros-systematic-review.org) to manage screening, assessment of full-text articles, and resolution of discrepancies.
We will present an adapted PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow-chart of study selection (Figure 1) (Liberati 2009).
Data extraction and management
For studies that fulfil inclusion criteria, two review authors (CB, CR) will independently extract data about relevant population and intervention characteristics using data extraction sheets entered in EROS and standard data extraction templates with any disagreements to be resolved by discussion, or, if required, by consultation with a third review author (GR) (for details see (for details see Table 1; Appendix 2; Appendix 3; Appendix 4; Appendix 5; Appendix 6; Appendix 7; Appendix 8; Appendix 9; Appendix 10; Appendix 11; Appendix 12; Appendix 13).
Table 1. Overview of study populations
|Characteristic||Intervention(s) and comparator(s)||Sample sizea||Screened/eligible|
|Randomized finishing study|
|(1) Study ID||CABG|| || || || || || || || || |
|PCI|| || || || || || || || || |
| || ||total:|| || || || || || || |
| || || || || || || || || || || |
| Grand total || All CABG interventions || || || ... || || || || ... || || |
| || All PCI c omparators || || || ... || || || || ... || || |
| || All interventions and c omparators || || || ... || || || || ... || || |
We will provide information including trial identifier about potentially relevant ongoing studies in the table 'Characteristics of ongoing studies' and in the appendix 'Matrix of study endpoints (trial documents)'. We will try to find the protocol of each included study, either in databases of trial registers or in publications of study designs, or both, and specify the data in the appendix 'Matrix of study endpoints (trial documents)'.
We will e-mail all authors of included studies to enquire whether they are willing to answer questions regarding their trials. We will present the results of this survey in Appendix 14. Thereafter, we will seek relevant missing information on the trial from the primary author(s) of the article, if required.
Furthermore, we will seek key unpublished information that is missing from reports of included studies.
Dealing with duplicate and companion publications
In the event of duplicate publications, companion documents or multiple reports of a primary study, we will maximize yield of information by collating all available data and use the most complete dataset aggregated across all known publications. In case of doubt, the publication reporting the longest follow-up associated with our primary or secondary outcomes will obtain priority.
Assessment of risk of bias in included studies
Two review authors (CB, CR) will assess the risk of bias of each included study independently. We will resolve disagreements by consensus, or by consultation with a third review author (GR).
We will assess risk of bias using The Cochrane Collaboration's tool for assessment of risk of bias (Higgins 2011a; Higgins 2011b). We will assess the following criteria in this assessment.
Random sequence generation (selection bias).
Allocation concealment (selection bias).
Blinding, separated for blinding of participants and personnel (performance bias) and blinding of outcome assessment (detection bias). Considering performance bias is almost impossible to avoid in the case of our intervention and comparison, we will evaluate if authors have taken any specific measure to address performance bias, including a detailed description of co-interventions.
Incomplete outcome data (attrition bias).
Selective reporting (reporting bias).
We will assess outcome reporting bias by integrating the results of 'Examination of outcome reporting bias' (Appendix 7), 'Matrix of study endpoints (trial documents)' (Appendix 6), and section 'Outcomes (outcomes reported in abstract of publication)' of the 'Characteristics of included studies' section (Kirkham 2010). This analysis will form the basis for the judgment of selective reporting (reporting bias).
We will judge 'Risk of bias' criteria as 'low risk', 'high risk', or 'unclear risk' and evaluate individual bias items as described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). We will present a 'Risk of bias' graph and a 'Risk of bias' summary figure.
We will assess the impact of individual bias domains on study results at endpoint and study levels.
For blinding of participants and personnel (performance bias), detection bias (blinding of outcome assessors), and attrition bias (incomplete outcome data), we intend to evaluate risk of bias separately for subjective and objective outcomes (Hróbjartsson 2013). We will consider the implications of missing outcome data from individual participants.
We will define the following endpoints as subjective outcomes.
Adverse events other than major bleeding and renal failure.
Any measure of severity of angina.
Health-related quality of life.
We will define the following outcomes as objective outcomes.
Nonfatal myocardial infarction.
Functional capacity measured by any method that is not operator-dependent, such as oxygen consumption, walking test.
Heart failure defined by echocardiographic assessment.
Binary restenosis rate.
Metabolic control (HbA1c).
Measures of treatment effect
We will express dichotomous data as risk ratios (RRs) with 95% confidence intervals (CIs). We will express continuous data as mean differences (MD) with 95% CI or standardized mean differences (SMDs) when measured in different scales.
Unit of analysis issues
We will take into account the level at which randomization occurred, such as multiple observations for the same outcome. Considering the nature of the intervention, it is unlikely that we will find cross-over trials or cluster randomized trials. If these are found, we will take unit of analysis into account.
Dealing with missing data
We will obtain relevant missing data from study authors, if feasible, and evaluate important numerical data such as screened, eligible, randomized participants as well as intention-to-treat (ITT), as-treated, and per-protocol (PP) populations. We will investigate attrition rates, for example drop-outs, losses to follow-up, and withdrawals, and critically appraise issues of missing data and imputation methods (e.g. last observation carried forward (LOCF)).
Where standard deviations for outcomes are not reported we will impute these values by assuming the standard deviation of the missing outcome to be the mean of the standard deviations from those studies where this information was reported. We will investigate the impact of imputation on meta-analyses by means of sensitivity analysis.
Assessment of heterogeneity
In the event of substantial clinical, methodological, or statistical heterogeneity, we will not report study results as meta-analytically pooled effect estimates.
We will identify heterogeneity by visual inspection of the forest plots and by using a standard Chi2 test with a significance level of α = 0.1, in view of the low power of this test. We will examine heterogeneity using the I2 statistic, which quantifies inconsistency across studies to assess the impact of heterogeneity on the meta-analysis (Higgins 2002; Higgins 2003), where an I2 statistic of 75% or more indicates a considerable level of inconsistency (Higgins 2011a).
When we find heterogeneity, we will attempt to determine potential reasons for it by examining individual study and subgroup characteristics.
We expect the following characteristics to introduce clinical heterogeneity.
Coronary acute syndrome versus chronic angina.
Number of vessels involved.
Medicated versus nonmedicated stents.
Strict versus nonstrict treatment of DM.
Assessment of reporting biases
If we include 10 studies or more that investigate a particular outcome, we will use funnel plots to assess small study effects. Owing to several possible explanations for funnel plot asymmetry, we will interpret results carefully (Sterne 2011).
Unless there is good evidence for homogeneous effects across studies, we will primarily summarize low risk of bias data using a random-effects model (Wood 2008). We will interpret random-effects meta-analyses with due consideration of the whole distribution of effects, ideally by presenting a prediction interval (Higgins 2009). A prediction interval specifies a predicted range for the true treatment effect in an individual study (Riley 2011). In addition, we will perform statistical analyses according to the statistical guidelines contained in the latest version of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a).
Subgroup analysis and investigation of heterogeneity
We will carry out the following subgroup analyses and plan to investigate interaction.
We will perform sensitivity analyses in order to explore the influence of the following factors on effect sizes.
Restricting the analysis to published studies.
Restricting the analysis by taking into account risk of bias, as specified in the section, Assessment of risk of bias in included studies.
Restricting the analysis to very long or large studies to establish the extent to which they dominate the results.
Restricting the analysis to studies using the following filters: diagnostic criteria, imputation, language of publication, source of funding (industry versus other), country.
We will also test the robustness of the results by repeating the analysis using different measures of effect size (RR, odds ratio (OR), etc.) and different statistical models (fixed-effect and random-effects models).